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Potential of Mesoporous Silica Nanoparticles for Applications in Targeted Treatment of Cancer

Authors: Mladenović, Minja; Mundžić, Mirjana; Pavlović, Aleksandra; Knežević, Nikola;

Potential of Mesoporous Silica Nanoparticles for Applications in Targeted Treatment of Cancer

Abstract

Background: Mesoporous silica nanoparticles (MSN) are being vastly demonstrated in the literature as efficient nanocarriers for cancer therapeutics. Their high surface area (ca. 1000 m2/g), well-structured porosity, versatile possibilities for obtaining nanocarriers of different morphologies, pore diameters and surface characteristics, allow construction of different nanosystems for efficient cancer targeting. Methods: In this study, the potential of mesoporous silica nanoparticles for applications in targeted treatment of cancer is presented. Results: Our team focuses on construction and surface functionalization of MSN with different moieties for active cancer-targeting. The drug release process can be also controlled through different externally applicable stimuli (eg. light irradiation, magnetic field), or upon exposure to intratumoral conditions such as weakly acidic environment, the elevated concentration of glutathione or other cancer biomarkers. In addition, MSN can be decorated with specific moieties to enable imaging of cancer (eg. magnetic resonance imaging (MRI)), which would enable simultaneous cancer therapy and diagnostics (theranostics). Conclusions: Mesoporous silica nanoparticles have substantial potentials for enhancing the efficacy and precision of cancer treatment.

Acknowledgments: The authors acknowledge financial support of the Science Fund of the Republic of Serbia (PROMIS Grant No. 6060755) and the European Union's Horizon 2020 research and innovation programme (Grant agreement No. 952259).

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Keywords

Mesoporous silica nanoparticles (MSNs), targeted anti-cancer drug delivery, nanocarriers

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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